Targeted advertisements from intended recipient predictions derived from user information

ABSTRACT

A method of generating a targeted advertisement by identifying a target criteria from an entry of a search history associated with a user, identifying an intended recipient based on social information associated with the user and the target criteria, and associating at least one item with the intended recipient by analyzing the social information and the target criteria. Further, the method includes outputting as advertisement information the at least one item and at least one of a plurality of advertisement recipients. The advertisement information enables the generation of the targeted advertisement and the at least one item is utilized in the targeted advertisement.

DOMESTIC PRIORITY

This application is a continuation of U.S. application Ser. No.14/496,286, filed on Sep. 25, 2014, the disclosure of which isincorporated by reference herein in its entirety.

BACKGROUND

The present disclosure relates generally to targeted advertising forpurchasable items, and more specifically, to generating targetedadvertisements based on intended recipient predictions, the intendedrecipient predictions being derived from user information.

In general, targeted advertising is when advertisements based on itemsof previous interest to a user are provided to that user while webbrowsing. Targeted advertising thus enables advertisers to directspecific advertisements to particular users who are more likely toengage with those specific advertisements. However, targetedadvertisements are often wasted on users who are not looking to purchasethe advertised product for a variety of reasons.

SUMMARY

Embodiments include a method, system, and computer program product foridentifying, by a processor, a target criteria of a search entry from asearch history associated with the online activity of a user;identifying, by the processor, an intended recipient based on socialinformation associated with the user and the target criteria;associating, by the processor, at least one item with the intendedrecipient by analyzing the social information and the target criteria.

Additional features and advantages are realized through the techniquesof the present invention. Other embodiments and aspects of thedisclosure are described in detail herein. For a better understanding ofthe invention with the advantages and the features, refer to thedescription and to the drawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The subject matter which is regarded as the invention is particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The forgoing and other features, and advantages ofthe invention are apparent from the following detailed description takenin conjunction with the accompanying drawings in which:

FIG. 1 illustrates an advertising system performing a targetedadvertising operation in accordance with an embodiment;

FIGS. 2-4 illustrate process flows of an advertising system inaccordance with an embodiment in accordance with an embodiment;

FIG. 5 illustrates a computing device schematic configured to performtargeted advertising operations in accordance with an embodiment;

FIG. 6 illustrates a process flow of an advertising system in accordancewith an embodiment;

FIG. 7-10 illustrate matching and/or association examples of anadvertising system in accordance with an embodiment;

FIGS. 11-13 are block schematics of different probability phases duringa targeted advertising operation of an advertising system in accordancewith an embodiment; and

FIG. 14 illustrates a processing system schematic configured to performtargeted advertising operations in accordance with an embodiment.

DETAILED DESCRIPTION

As indicated above, targeted advertisements can be wasted on users whoare not looking to purchase the advertised product. Embodimentsdescribed herein can avoid wasting targeted advertising by providingtargeted advertisements to users based on predictions about intendedrecipients of previously purchased products and presently browsedproducts. These predictions can be derived based on information gatheredfrom a purchase transaction, search history data, social information,and other sources.

Embodiments will now be described with reference to FIG. 1 by utilizinga representative example of an advertising system 100. In general, theadvertising system 100 through exploitation of social networksidentifies an intended recipient of a gift that was purchased or ofitems that are being browsed (e.g., a gift). Determining who a gift oritem is for, or rather, a determined intended recipient can then beutilized to render improved targeted advertisements served to a buyer(e.g., or a purchaser/user/browser/potential buyer/etc.). For example,an advertiser may utilize an advertisement schedule to sendadvertisements to a market; however, by utilizing a rubric that relieson the intended recipient, the advertising system may store timinginformation for future use. For example, targeted advertisement for“gifts for a nephew of 4 years old” should be stopped shortly after thatnephew's birthday party. Similarly, targeted advertisement for “giftsfor a visiting friend” should be stopped after the friend has concludedtheir visit. Further, when the advertising system 100 identifies byleveraging social networks that a gift was for a niece on her birthday,the advertising system may at 11 to 12 months from the purchase of thegift show advertisements regarding birthday gifts for that niece to theuncle who purchased the gift. In turn, the time between the birthday andthe 11 month mark may be filled with other targeted advertisements bythe advertising system 100. In addition, by leveraging social networks,the advertising system 100 may discover preferences of the niece andenhance the subsequent round of targeted advertisements with thepreferences. For instance, when the advertising system 100 detects thata social network page of the niece—lists that she is a pacifist, thenadvertisements by the advertising system 100 regarding plastic armyweapons will be filtered out of targeted advertisements to the uncle andothers related to the uncle (e.g., aunt/wife, mom/grandmother,son/cousin, etc.), as indicated by the social networks.

Further, the advertising system 100 can improve targeted advertising bymonitoring a user's behavior. In one example, the advertising system 100gathers and accumulates information regarding which people in a user'ssocial graph are recipients of gifts. Thus, when the advertising system100 detects that a user bought a gift for a close relative for aholiday, the advertising system 100 can assume that each year at asimilar time the user will buy another gift for the same close relative.Further, the advertising system 100 gathers and accumulates informationregarding all of the people that a user buys for during a year, and thenas the Christmas or other holiday season arrives, the advertising system100 renders targeted advertisements to the user regarding each of thosepeople.

The advertising system 100 can also improve the advertising to a gifttarget based on the gift target themselves, product/services that a userrelated to the gift target is browsing, and/or a purpose of the gift(e.g., gift purpose or target criteria). For example, if a user isbrowsing for a birthday gift, once the advertising system 100 identifiesan intended recipient, then that intended recipient may be providedtargeted advertisement related to birthday party catering. Further, oncea product is purchased by the user, the advertising system 100 maygenerate follow-on targeted advertisements for the intended recipient(e.g., if the user purchases a smart phone, then the intended recipientmay receive follow-on targeted advertisements related to screenprotectors, protecting cases, etc., while the intended recipient may noteven realize that the smart phone has been purchased for them).

Additionally, the advertising system 100 can employ a refined graphsearch procedure to generate search suggestions and other passiveconfirmation techniques to interactively narrow down or filter a set ofcandidate recipients, and further narrow down the set of candidaterecipients based on upcoming events for each of the candidate recipientsthat may indicate that they are likely to receive gifts (e.g., birthday,wedding, etc.). The advertising system 100 can refine a content andduration of the advertising displayed to the purchaser or potentialpurchaser based on the person and the event that the item is beingpurchased for and utilizes the actions of the purchaser to influence thecontent, timing, and duration of the advertisements displayed to thepurchaser, user connected to the purchaser, and intended recipient.Refinement of searches, content, duration, etc. may include utilizingproduct information to derive probability estimations for targetcriteria, intended recipients, product/service suggestions,advertisement recipients, advertisement timing, and the like, as furtherdescribed below.

Returning to FIG. 1, the advertising system 100 includes userinformation 102, which includes data conveyed either as a content of amessage or through direct or indirect observation of some activity fromwhich knowledge of a particular person can be derived. Examples of theuser information 102 include search history 103, purchase history 104,and social data 105. Search history 103 comprises a list of web pagesand associated data, such as page title, time of visit, etc. Purchasehistory 104 comprises a list of products/services and associated data,such as product/services title, value of purchase, time of purchase,etc. Social data 105 comprises information relating to and describingusers and interactions between users, such as gender, age, career,interests, calendar events, relationship status, relationshipinformation, etc. As illustrated in FIG. 1, examples of the userinformation 102 include a doll and a fairy costume as the search history103, an Easy-Bake Oven as the purchase history 104, and indications thatAddison's Birthday is pending and that Addison had a youth soccer gameas social data 105.

The advertising system 100 can also include product information (notshown) that describes aspects of each product or service, such as aproduct/service name, manufacturer, provider, origination, warrantee,target demographic, age group, price, lifespan, durability, components,reviews, etc. Further, product information may include a provider'sdescription that indicates an item's (e.g., product/service) targetaudience, based on the item's design/age/requirements/gender/etc. Forexample, a manufacturer's description may indicate that an ‘Easy-BakeOven’ should be marketed and sold to young females.

The advertising system 100 also includes a predictive advertisingheuristic 106 that implements the above features of the intendedrecipient identification, the targeted advertising based on behaviormonitoring, the targeted advertisement to a gift target, the refinedgraph search procedure, and/or the refined advertising displayed to thepurchaser or potential purchaser. In one operational example, thepredictive advertising heuristic 106 receives (e.g., Arrows A) userinformation 102 that is utilized to output (e.g., Arrows B)advertisement information, which supports the generation of targetedadvertisements by the advertising system 100. For instance, in responseto and in accordance with a search for a product/services by a purchaseror potential purchaser, the predictive advertising heuristic 106acquires (e.g., Arrow A) the search history 103, the purchase history104, and the social data 105 as the user information 102. Note that userinformation 102 may be continuously received/acquired in real-time sothat the predictive advertising heuristic 106 may utilize the mostrecent user information 102 in generating advertisement information orin batches so as to preserve network and processing resources.

Next, in block 107, the predictive advertising heuristic 106 proceeds toprocess the user information 102 to determine an intended recipient.That is, when an item (e.g., product/service) is purchased or browsed bya user, the predictive advertising heuristic 106 determines an intendedrecipient of this item (e.g., who is a gift target, is this a gift to mynephew, is this a gift to myself, etc.) by analyzing search history 103,purchase history 104, and/or the social data 105. Further, when multiplegift targets are identified, a probability will be calculated for eachtarget. For example, the predictive advertising heuristic may confirmwith the user when there are multiple gift targets. This confirmationmay be done explicitly or passively. Explicit confirmation may includeasking the user to provide input that identifies the gift target.Passive confirmation may include refining or augmenting a search engineby providing search suggestions, such as “other people specificallysearch for 4 years old boy” and/or “other people specifically search for6 years old girl.”

FIG. 2 illustrates one example of a process flow 200 of determining anintended recipient. In block 201, the predictive advertising heuristic106 determines a list of upcoming events that surround a user. Then inblock 203, for each event, the predictive advertising heuristic 106identifies one or more gift targets (e.g., a human, a pet, or anexhibition) of each event, which may be computed from the social data105. In block 205, the predictive advertising heuristic 106 associateszero or more upcoming events with each item (e.g., collected from asearch query or the browsed products/services indicated in the searchhistory 103). For each upcoming event, in block 207, the predictiveadvertising heuristic 106 determines a count of the associated itemswithin a time period (e.g. 1 hours, 1 day, 1 week, 2 weeks, etc.). Then,in block 209, the predictive advertising heuristic 106 determines apotential interest of the user in each event in accordance with thecount. The interest of the user in joining a specific event, and theinterest in bringing a gift to the event could further supplemented byother social network data, or confirmation from electronic invitationservice (e.g. evite.com).

In another example of determining the intended recipient, the predictiveadvertising heuristic 106 may analyze the user information 102 toidentify target criteria of the product/service search and associate theintended recipient with the target criteria. For example, the predictiveadvertising heuristic 106 identifies that the purchaser who searches forthe doll and the fairy costume along with previously purchasing anEasy-Bake Oven may be searching for a gift for a young girl anddetermines the young girl (e.g., or female child between age 5 and 10)to be the target criteria. Further, the predictive advertising heuristic106 analyzes the target criteria in view of the indication by the socialdata 105 of Addison's pending birthday to determine that the intendedrecipient is likely Addison.

In conjunction with determining the intended recipient, the predictiveadvertising heuristic 106 generates, updates, and/or accesses databases(e.g., block 108 of FIG. 1) to produce product/service suggestions. Thatis, because the user information 102 may be continuouslyreceived/acquired in real-time or in batches, the predictive advertisingheuristic 106 may stores the received/acquired user information 102,along with product information of products/services. In turn, the userinformation 102 and the product information of the databases so that maybe utilized as needed for product/service suggestions, as furtherdescribed below with respect to FIG. 3.

FIG. 3 illustrates one example of a process flow 300 of generating adatabase of items (e.g., products/services), and associatedmarket/audience through crowd sourcing. In block 301, for each itembrowsed by a user, the predictive advertising heuristic 106 tags thatitem with an event or event type together with a determined probability.Then, in block 303, for each item browsed by the user, the predictiveadvertising heuristic 106 tags each item type with the event or theevent type together with the determined probability. Next, in block 305and 307, when multiple inputs are collected from multiple users, thepredictive advertising heuristic 106 generates for each item a list ofassociated event types and determines an overall probability for eachevent type.

In another example of generating databases, the predictive advertisingheuristic 106 may automatically identify and store in the databases thatthe purchaser searched for the doll and the fairy costume along withpreviously purchasing an Easy-Bake Oven based in the search and purchasehistories 103, 104. Further, the predictive advertising heuristic 106may, based on the social data 105, automatically identify and store inthe databases that the intended recipient is Addison, that the purchaseris an uncle to Addison, that the uncle recently checked into Addison'ssoccer game, and that an interest of Addison includes the color green.Next, when the databases are accessed by the predictive advertisingheuristic 106 to assist in determining product suggestions for abirthday gift for Addison, the predictive advertising heuristic 106 mayidentify as product suggestions for future targeted advertisements apopular princess doll, based on the uncle's previous searches, and/or agreen soccer ball, based on Addison's interest.

The predictive advertising heuristic 106 further utilizes (e.g., blocks109 and 110 of FIG. 1) the intended recipient and the productsuggestions to determine a plurality of advertisement recipients and thetiming of each advertisement to those recipients, each of which ispackaged as advertisement information that is utilized to generatetargeted advertisements by the advertising system 100. For instance,based on the social data 105, the predictive advertising heuristic 106identifies as advertisement recipients a wife of the uncle, who islikely also an aunt to Addison, and a mother of the uncle, who is likelyalso a grandmother of Addison. Note that advertisement recipients mayalso be referred to as each potential purchasers. Next, the predictiveadvertising heuristic 106 determines as advertisement timing that theuncle, the aunt, and the grandmother should immediately receiveadvertisements for the popular princess doll and the soccer ball. Then,the predictive advertising heuristic 106 outputs (e.g., Arrow B)advertisement information that includes the intended recipient, theproduct suggestions, the advertisement recipients, and the advertisementtiming, each of which is utilized by the advertising system 100 and/orexternal system to generate targeted advertisements.

In addition, if at any time the most recent user information 102indicates a change in the conduct of the intended recipient and/orindicates alternative product suggestions, recipients, and/or timing,then the predictive advertising heuristic 106 may update theadvertisement information accordingly. For example, if the most recentuser information 102 indicates that the uncle has purchased the greensoccer ball and that the grandmother and the aunt have purchased giftsother than those mentioned above for Addison for her upcoming birthday(e.g., such as in an email or social network message), then thepredictive advertising heuristic 106 may send targeted advertisementswith respect to the popular princess doll to each potential purchaser ata different advertisement timing, such as during an upcoming holidayseason.

In another example, the predictive advertising heuristic 106 isconfigured to use a gift target's social network information, enhance anexperience of potential purchasers and gift targets through searchengine augmentation, and create highly targeted advertisement. FIG. 4illustrates one example of a process flow 400 where, in block 401, basedon at least one gift target, the predictive advertising heuristic 106determines a purpose of a gift (e.g., target criteria). In block 403,based on at least the gift target and/or the target criteria, thepredictive advertising heuristic 106 determines a future advertisementschedule for a user. In block 405, based on at least the gift targetand/or the target criteria, the predictive advertising heuristic 106determines a behavior of the user. In block 406, based on at least anitem (e.g., products/services) that the user is browsing, the gifttarget, and/or the target criteria, the predictive advertising heuristic106 generates at least one targeted advertisement for at least onepotential purchaser. In block 407, based on at least the productpurchased by the user and the gift target, the predictive advertisingheuristic 106 generates at least one follow-on advertisement for thegift target. In block 409, based on at least one gift target, thepredictive advertising heuristic 106 augments searches for items on allavailable interfaces, such as search queries on a general search engineand searches on product website, to provide better search result.

The advertising system 100 and elements therein may take many differentforms and include multiple and/or alternate components and facilities.For instance, the advertising system 100 may include and/or employ anynumber and combination of computing devices and networks utilizingvarious communication technologies, as described above, that enable theadvertising system 100 to query and retrieve information in support ofgenerating targeted advertisements. While the advertising system 100 isshown in FIG. 1, the components illustrated in FIG. 1 are not intendedto be limiting. Indeed, additional or alternative components and/orimplementations may be used. In one example, the advertising system 100may generally be included within a computing device employing a computeroperating system, such as one of those mentioned above, as shown in FIG.5.

FIG. 5 illustrates a computing device 500 (e.g., a computing device asdescribed below) configured to provide a targeted advertising processthat includes a processor 502, an input/output interface 503, and amemory 504. The processor 502 may receive computer readable programinstructions from the memory 504 and execute these instructions, therebyperforming one or more processes defined by an advertising application510.

The processor 502 may include any processing hardware, software, orcombination of hardware and software utilized by the computing device500 that carries out the computer readable program instructions byperforming arithmetical, logical, and/or input/output operations.Examples of the processor 502 include, but are not limited to anarithmetic logic unit, which performs arithmetic and logical operations;a control unit, which extracts, decodes, and executes instructions froma memory; and an array unit, which utilizes multiple parallel computingelements.

The input/output (I/O) interface 503 may include a physical and/orvirtual mechanism utilized by the computing device 500 to communicatebetween elements internal and/or external to the computing device 500.That is, the I/O interface 503 may be configured to receive or sendsignals or data within or for the computing device 500. An example ofthe I/O interface 503 may include a network adapter card or networkinterface configured to receive computer readable program instructionsfrom a network and forward the computer readable program instructions,original records, or the like for storage in a computer readable storagemedium (e.g., memory 504) within the respective computing/processingdevice (e.g., computing device 500).

The memory 504 may include a tangible device that retains and storescomputer readable program instructions, as provided by the advertisingapplication 510, for use by the processor 502 of the computing device500.

The advertising application 510 includes computer readable programinstructions configured to provide accurate determinations of an‘intended recipient of a purchased product or service’ such thatadvertisers would have a better ability to target advertisements to apurchaser of a future product/service and a future recipient. That is,the advertising application 510 utilizes a predictive advertising module514 to respond to a search for an item by a purchaser or potentialpurchaser by acquiring and analyzing from a storage database 530 userinformation 533, 534, 535 and product information (as further describedbelow).

The predictive advertising module 514 includes computer readable programinstructions configured to implement the above features of the intendedrecipient identification, the targeted advertising based on behaviormonitoring, the targeted advertisement to a gift target, the refinedgraph search procedure, and/or the refined advertising displayed to thepurchaser or potential purchaser.

While single items are illustrated for the application 510 (and otheritems) by FIG. 5, these representations are not intended to be limitingand thus, the application 510 items may represent a plurality ofapplications. For example, multiple advertising applications indifferent locations may be utilized to access the collected information(e.g., user information), and in turn those same applications may beused for on-demand data retrieval and targeted advertisement generation.In addition, although one modular breakdown of the application 510 isoffered, it should be understood that the same operability may beprovided using fewer, greater, or differently named modules. Although itis not specifically illustrated in the figures, the applications 510 mayfurther include a user interface module and an application programmableinterface module; however, these modules may be integrated with any ofthe above named modules. A user interface module may include computerreadable program instructions configured to generate and mange userinterfaces that receive inputs and present outputs. An applicationprogrammable interface module may include computer readable programinstructions configured to specify how other modules, applications,devices, and systems interact with each other.

The storage database 530 may include a database, data repository orother data store and may include various kinds of mechanisms forstoring, accessing, and retrieving various kinds of data, including ahierarchical database, a set of files in a file system, an applicationdatabase in a proprietary format, a relational database managementsystem (RDBMS), etc. The storage database 530 may include a database, asdescribed above, capable of storing user information 533, 534, 535 andproduct information (not shown). The storage database 530 is incommunication with the application 510 of and/or applications externalto the computing device 500, such that user information 533, 534, 535embodied as data instances, data structures, and documents includingdata structures may be collected and archived in support of theprocesses described herein (e.g., advertising process). In operation,for example, the storage database 530 may collect and archive userinformation 533, 534, 535 received from any system or sub-systemexternal to the storage database 530. As illustrated in FIG. 5, thestorage database 530 includes a plurality of user information 533, 534,535, illustrated as search history instances 533.0 to search historyinstances 533.n, purchase history instances 534.0 to purchase historyinstances 534.n, and social network information instances 535.0 tosocial network information instances 535.n (e.g., calendar and userrelationship information), where ‘n’ is an integer representing a numberstructures archived by the storage database 530. Although one numberingsequence for the records of the storage database 530 is offered, itshould be understood that the same operability may be provided usingfewer, greater, or differently implemented sequences. The storagedatabase 530 may be a part of the advertising application 510, runindependently within the same device or system as the advertisingapplication 510 (as illustrated in FIG. 5), or be an external to and incommunication with, via a network in any one or more of a variety ofmanners, the advertising application 510. The storage database 530 mayfurther communicate with other systems that may be internal or externalto computing device 500 to collect and archive the user information 533,534, 535.

The advertising system, method, and/or computer program as embodied inthe computing device 500 will be described with reference to FIGS. 6-10.FIG. 6 illustrates a process flow 600 of the advertising application510. The process 600 illustrates a set of operation blocks that are notlimiting an order or grouping of operation blocks. In fact, theoperation blocks may be executed in sequence, concurrently, or theoperation blocks may sometimes be executed in the reverse order,depending upon the operability involved.

The process 600 begins, at block 605, when the application 510identifies target criteria (e.g., gift purpose) of a product/servicesearch by a potential purchaser, which may include a singular search fora singular product/service or a combination of searches for multipleproducts/services and/or variations on those products/services. Theproduct/service search may be provided to the application 510 inreal-time and/or acquired by the application 510 from the userinformation 533, 534, 535 of the database 530. For instance, theapplication 510 receives the search history instances 533.0-533.nassociated with a user (e.g., the purchaser or the potential purchaser)of the computing device 500, identifies target criteria for the items ofthe each search instance 533.0-533.n, and computes a probability thatthe identified target criteria correctly matches the items.

FIG. 7 illustrates an example of matching items of a search history 703and instances of target criteria 740, along with computed probabilityassociations for each match. The items of the search history 703 include‘Lion King tickets,’ ‘Broadway musical tickets,’ ‘Golden dragon legoset,’ ‘Ninjago lego sets,’ ‘Doll,’ and ‘Princess costume.’ The instancesof the target criteria 740 include an ‘Anniversary gift,’ ‘Boy'sbirthday gift,’ and a ‘Girl's birthday gift.’ As illustrated, theapplication 510 computes which item is in relation to which criteriainstance. In this case, based on product information and/or userinformation 533, 534, 535, the ‘Lion King tickets’ and ‘Broadway musicaltickets’ are matched with the ‘Anniversary gift;’ the ‘Golden dragonlego set’ and ‘Ninjago lego sets’ are matched with the ‘Boy's birthdaygift;’ and the ‘Doll,’ and ‘Princess costume’ are matched with the‘Girl's birthday gift.’

For instance, because the product information defines the ‘Lion Kingtickets’ and ‘Broadway musical tickets’ as fun for the whole family,both products are estimated to have a 100% probability of being an‘Anniversary gift,’ while having an estimated a 50% probability of beinga ‘Boy's birthday gift’ or a ‘Girl's birthday gift.’ Because the productinformation defines the ‘Golden dragon lego set’ and the ‘Ninjago legosets’ as targeted to male children between the ages of 5 and 10, theseproducts are estimated to have a 100% probability of being a ‘Boy'sbirthday gift’ and a 17% probability of being a ‘Girl's birthday gift.’Also, because the product information defines the ‘Doll’ and ‘Princesscostume’ as targeted to only female children between the ages of 5 and10, these products are estimated to have a 100% probability of being a‘Girl's birthday gift’ and a 0% probability of being a ‘Boy's birthdaygift.’ Since the children's gifts are not defined by product informationas targeted to adults, both products have a 0% probability of being an‘Anniversary gift.’

At block 610, the application 510 may modify the target criteria 740based on an analysis of the user information 533, 534, 535, as seen inFIG. 8. FIG. 8 illustrates a search history 803, which is a re-orderedversion of the search history 703 according to which product thepotential purchaser is likely to purchase, matched to modified criteria840. In the FIG. 8 scenario, the application 510 analyzed the targetcriteria 740 in view of purchase history instances 534.0-534.n relatedto the purchaser to produce the modified criteria 840. For example, whena purchase history indicates that the purchaser has purchased ‘PhantomOf The Opera tickets,’ the application 510 computes that an ‘Anniversarygift’ has already been purchased. Further, the application 510 computes,based on calculated probabilities, that the purchaser was alsoconducting the product search for a ‘Girl's birthday gift.’ In turn,both the ‘Anniversary gift’ and ‘Boy's birthday gift’ are removed fromthe target criteria 740 to produce the modified criteria 840, whichindicate at least one gift purpose.

Next, the process 600 proceeds to block 615 where the application 510acquires or generates an intended recipient list based on socialinformation 535 and the modified criteria 840. For example, by utilizingthe social information instances 535.0-535.n, the application 510identifies that the purchaser is connected via family relationships tomultiple female children, such as a niece Addison, a daughter Bertha,and a cousin Courtney. Since these three children fit the modifiedcriteria 840, they are included in the intended recipient list.

The application 510 may further utilize other information, such assearch history instances 533.0-533.n and purchase history instances534.0-534.n, to acquire or generate an intended recipient list. Forinstance, in another example, the application 510 determines theintended recipient of an ‘Easy_bake_oven.’ In this example, the searchhistory instances 533.0-533.n contain ‘Cabbage_patch,’‘Car_rental_in_Vegas,’ ‘China_patterns,’ ‘Cufflinks,’ ‘Hotels,’‘Luggage,’ ‘Nintendo_DS,’ ‘Picture_Frames,’ and ‘Tricycle;’ the purchasehistory instances 534.0-534.n contain ‘Easy_bake_oven;’ and the socialdata, which is gathered from the purchaser's social network and/orsocial information instances 535.0-535.n, contains the followingcalendar events: ‘Vacation_to_Vegas,’ ‘Wedding,’‘Birthday_party_for_niece.’

Further, in operation, the application 510 associates each searchhistory instance 533.0-533.n with a gift purpose, so that each searchinstance can be categorized according to a gift target of a user'sbrowsing. Then, the application 510 associates the calendar events witheach search instance via the categorization so that an intendedrecipient may be identified. For example, FIG. 9 illustrates a matchingof instances of the search history 903 by the application 510 tocategories of the target criteria list 935. Then, in FIG. 9, theinstances of the target criteria list 935 are matched to each event ofthe calendar list 940, so that each event of the calendar list 940 isassociated with at least one instance of the search history 903. Notethat while one set of matching is depicted in FIG. 9, there may be someoverlap between the matching (e.g., ‘luggage’ could be a wedding gift orsomething you need for a vacation, and therefore falls into bothcategories).

In another example of the application 510, FIG. 10 illustrates anassociation between a search history 1003 and social information 1005,where multiple products are associated with multiple social events(e.g., the items browsed by the user can be mapped to these events). InFIG. 10, a search history 1003 includes the products of ‘Legos,’‘Perfumes,’ ‘Wine,’ ‘Vases,’ ‘Musical gift vouchers,’ ‘Restaurant giftvouchers,’ and ‘Spa gift vouchers.’ The social information 10005includes the social events of ‘Joey's 6th B'day party—In 3 weeks,’‘Cousin Sam's 20th B'day bash—In 1 week,’ and ‘John-Julie 25^(th)Anniversary—In 6 weeks,’ each of which may be based on calendarinformation of the social information 1005. Note that in FIG. 10, theevent with the most count (e.g., 6) would be the event for which theuser is most interested in buying a gift and thus advertisement may beshown for this event. That is, the advertisements are based an eventthat the user is most interested in and, in FIG. 10, the John-Julie25^(th) Anniversary event have the most associated interest.

The determination of these categories or groups may also be obtainedfrom the product information and/or by suggestions of a search engineutilized for browsing, such as toys for small children, wedding giftideas, trip planning Further, crowd sourcing may be utilized by theapplication 510 for the categorization of data. That is, when purchasingan item, a pop-up with a question requesting a purpose of the purchasemay be used to gather data, such as ‘Is this item for a vacation?’ or‘Is this for a child?’ Also, a drop down list soliciting a selection(e.g., from a list including man, woman, child, co-worker, friend, etc.and/or Graduation/Birthday/Wedding) may be utilized by the application510 to collect data and refine categories. Thus, by using aconglomeration of many purchases, the application is able to understandthe purpose of each purchase.

Next, the application 510 utilizes the categorization to discover theintended recipient of the purchase history item of ‘Easy_bake_oven.’That is, because the ‘Easy_bake_oven’ is most likely to be in a smallchild category, the ‘Easy_bake_oven’ is associated with calendar eventpreviously assigned to that category. In this example, the application510 thus classifies the ‘Easy_bake_oven’ as a purchased item under thecalendar event of ‘Birthday party for niece.’ Moreover, the application510 then determines that person associated with the ‘Birthday party forniece’ is Addison; therefore, the intended recipient of the‘Easy_bake_oven’ is likely to be Addison. Thus, the intended recipientlist in this example includes at least one person.

Then, at block 620, the application filters the intended recipient listbased on the social information instances 535.0-535.n and the modifiedcriteria 840 to produce a filtered list. For example, because the socialinformation instances further indicate that Addison has a pendingbirthday, while Bertha's and Courtney's respective birthdays havepassed, Bertha and Courtney are filtered from the intended recipientlist to produce a filtered list of at least one intended recipient(e.g., Addison).

Next, the process 600 proceeds to block 625 where the application 510utilizes the user information 533, 534, 535 to generate a productdatabase that is associated with each person of the filtered list. Inthe above case, because Addison is the only person on the filtered list,the product list will directly relate to Addison and her pendingbirthday. Thus, for example, when the social information instances535.0-535.n indicate that Addison has interests in soccer and the colorgreen and the products of the search history 533 include a number ofproducts with a probability association above a certain threshold (e.g.,above 51%), a product list including a ‘green soccer ball,’ a ‘doll,’and a ‘princess costume’ is generated by the application 520.

At block 630, the application 510 determines and/or outputsadvertisement information, in accordance with the filtered list and theproduct list, which enables the generation of targeted advertisements.Particularly, the application 510 utilizes the intended recipient todynamically influence in real-time frequencies, durations, and contentsof targeted advertisements displayed to the purchaser while thepurchaser continues shopping. For instance, the application maydetermine through an analysis of the social information instances535.0-535.n that the potential purchaser is an uncle to Addison.Further, the uncle and Addison are both determined to be connected to atleast two other adults (e.g., a wife/aunt and mother/grandmother). Inthis way, the advertisement information is utilized by the application510 to deliver targeted advertisements to each adult, while Addison'sbirthday is pending. Thus, the application may generate and provide atargeted advertisement for a soccer ball during subsequent internetbrowsing by the uncle, a targeted advertisement for a doll duringsubsequent internet browsing by the aunt, a targeted advertisement for aprincess costume during subsequent internet browsing by the grandmother,and/or any combination thereof.

Then, the process 600 ends.

The advertising system, method, and/or computer program will now bedescribed, with reference to the advertising system 100 of FIG. 1, inFIGS. 11-13.

FIGS. 11-13 are block schematics of different probability phases duringa targeted advertising operation of an advertising system. Particularly,FIGS. 11-13 describe a use case where, based on a gift target, theadvertising system 100 determines target criteria and utilizes thattarget criteria to enhance targeted advertisement decisions, such as theadvertisement duration. As indicated in FIG. 11, the advertising system100 detects that an item (e.g., China Set of purchase history 1104) hasbeen purchased. If the social data 1140 indicates that a variety ofevents (e.g., Birthday Party, Wedding, and Visiting Friend) are pendingfor the purchaser, the advertising system 100 then determines and/orassociates an even probability (e.g., 33%) for each event when it has nofurther information. Then, in FIG. 12, when the advertising system 100determines, by analyzing an additional purchase history of thepurchaser, that an Easy-Bake Oven was also purchased, the advertisingsystem 100 may then compute that the Easy-Bake Oven has a gift purposeof a birthday gift. The advertising system 100, therefore, reduces theprobability that the China Set is also for the Birthday Party event(e.g., to a nominal 2%) while increasing the probability that the ChinaSet is for the other events (e.g., 49% respectively). Next, in FIG. 13,when the advertising system 100 determines that a visit with a friendhas passed, then the advertising system 100 reduces the probability ofthe Visiting Friend event (e.g., 0%). In turn, the Wedding event isproportionally increased (e.g., 90%). Thus, the advertising system 100has computed that the China Set has a very high probability of being forthe Wedding event in relation to the other events.

In view of the above, the advertising system, method, and/or computerprogram product is a significant improvement over inappropriate orincorrectly targeted advertisements based on a user's interaction withinformation. Particularly, the advertising system, method, and/orcomputer program enables future pre-scheduled advertisement with anunderstanding of a gift target and a gift purpose (e.g., “what's theoccasion”). In addition, the advertising system, method, and/or computerprogram utilizes a user's understanding of the gift target's preferences(e.g., through the data analytics) to influence the user's selection ofgift. In other works, the advertising system, method, and/or computerprogram is looking at a more than a user's social network and assuming agift purchase; the advertising system, method, and/or computer programcombines the social data from social networks, purchase history, andbrowsing history to determine if they are likely to be purchasing agift, and if so then we likely know who it is for.

Referring now to FIG. 14, there is shown another embodiment of aprocessing system 1400 for implementing the teachings herein. Systemsand/or computing devices, such as advertising system (e.g., advertisingsystem 100 of FIG. 1, computing device 500 of FIG. 2, and processingsystem 1400 of FIG. 14), may employ any of a number of computeroperating systems, including, but by no means limited to, versionsand/or varieties of the AIX UNIX operating system distributed byInternational Business Machines of Armonk, N.Y., the Microsoft Windowsoperating system, the Unix operating system (e.g., the Solaris operatingsystem distributed by Oracle Corporation of Redwood Shores, Calif.), theLinux operating system, the Mac OS X and iOS operating systemsdistributed by Apple Inc. of Cupertino, Calif., the BlackBerry OSdistributed by Research In Motion of Waterloo, Canada, and the Androidoperating system developed by the Open Handset Alliance. Examples ofcomputing devices include, without limitation, a computer workstation, aserver, a desktop, a notebook, a laptop, a network device, a handheldcomputer, or some other computing system and/or device.

In this embodiment, the processing system 1400 has one or more centralprocessing units (processors) 1401 a, 1401 b, 1401 c, etc. (collectivelyor generically referred to as processor(s) 1401). Processors 1401, alsoreferred to as processing circuits, are coupled to system memory 1414and various other components via a system bus 1413. Read only memory(ROM) 1402 is coupled to system bus 1413 and may include a basicinput/output system (BIOS), which controls certain basic functions ofthe processing system 1400. The system memory 1414 can include ROM 1402and random access memory (RAM) 1410, which is read-write memory coupledto system bus 1413 for use by processors 1401.

FIG. 14 further depicts an input/output (I/O) adapter 1407 and a networkadapter 1406 coupled to the system bus 1413. I/O adapter 1407 may be asmall computer system interface (SCSI) adapter that communicates with ahard disk 1403 and/or tape storage drive 1405 or any other similarcomponent. I/O adapter 1407, hard disk 1403, and tape storage drive 1405are collectively referred to herein as mass storage 1404. Software 1420for execution on processing system 1400 may be stored in mass storage1404. The mass storage 1404 is an example of a tangible storage mediumreadable by the processors 1401, where the software 1420 is stored asinstructions for execution by the processors 1401 to perform a method,such as the process flows of FIGS. 2-4 and 6. Network adapter 1406interconnects system bus 1413 with an outside network 1416 enablingprocessing system 1400 to communicate with other such systems. A screen(e.g., a display monitor) 1415 is connected to system bus 1413 bydisplay adapter 1412, which may include a graphics controller to improvethe performance of graphics intensive applications and a videocontroller. In one embodiment, adapters 1407, 1406, and 1412 may beconnected to one or more I/O buses that are connected to system bus 1413via an intermediate bus bridge (not shown). Suitable I/O buses forconnecting peripheral devices such as hard disk controllers, networkadapters, and graphics adapters typically include common protocols, suchas the Peripheral Component Interconnect (PCI). Additional input/outputdevices are shown as connected to system bus 1413 via user interfaceadapter 1408 and display adapter 1412. A keyboard 1409, mouse 1440, andspeaker 1411 can be interconnected to system bus 1413 via user interfaceadapter 1408, which may include, for example, a Super I/O chipintegrating multiple device adapters into a single integrated circuit.

Thus, as configured in FIG. 14, processing system 1400 includesprocessing capability in the form of processors 1401, and, storagecapability including system memory 1414 and mass storage 1404, inputmeans such as keyboard 1409 and mouse 1440, and output capabilityincluding speaker 1411 and display 1415. In one embodiment, a portion ofsystem memory 1414 and mass storage 1404 collectively store an operatingsystem such as the AIX® operating system from IBM Corporation tocoordinate the functions of the various components shown in FIG. 14.

In general, embodiments described herein provide determinations of anintended recipient of a purchased product or service such thatadvertisers can have a better ability to target advertisements to apurchaser of a future product/service. Embodiments can be used todetermine the intended recipient while an online user (e.g., apurchaser) is shopping for that product/service. After the intendedrecipient has been identified, embodiments can utilize the intendedrecipient to dynamically influence, in real-time, frequencies,durations, and contents of targeted advertisements displayed to thepurchaser while the purchaser continues shopping, along with thoseconnected to the purchaser and the intended recipient. Thus, bydetermining who the intended recipient is, embodiments can be utilizedto provide business value for advertisers seeking to increase theeffectiveness of their targeted advertisements.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention. The computer readable storage medium can be atangible device that can retain and store instructions for use by aninstruction execution device.

Computer readable storage mediums may be a tangible device that retainsand stores instructions for use by an instruction execution device(e.g., a computing device as described above). A computer readablestorage medium may be, for example, but is not limited to, an electronicstorage device, a magnetic storage device, an optical storage device, anelectromagnetic storage device, a semiconductor storage device, or anysuitable combination of the foregoing. A non-exhaustive list of morespecific examples of the computer readable storage medium includes thefollowing: a portable computer diskette, a hard disk, a random accessmemory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM or Flash memory), a static random access memory(SRAM), a portable compact disc read-only memory (CD-ROM), a digitalversatile disk (DVD), a memory stick, a floppy disk, a mechanicallyencoded device such as punch-cards or raised structures in a groovehaving instructions recorded thereon, and any suitable combination ofthe foregoing. A computer readable storage medium, as used herein, isnot to be construed as being transitory signals per se, such as radiowaves or other freely propagating electromagnetic waves, electromagneticwaves propagating through a waveguide or other transmission media (e.g.,light pulses passing through a fiber-optic cable), or electrical signalstransmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network (e.g., any combination of computing devices andconnections that support communication). For example, a network may bethe Internet, a local area network, a wide area network and/or awireless network. The network may comprise copper transmission cables,optical transmission fibers, wireless transmission, routers, firewalls,switches, gateway computers and/or edge servers. A network adapter cardor network interface in each computing/processing device receivescomputer readable program instructions from the network and forwards thecomputer readable program instructions for storage in a computerreadable storage medium within the respective computing/processingdevice.

Computer readable program instructions may be compiled or interpretedfrom computer programs created using assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on a computingdevice, partly on the computing device, as a stand-alone softwarepackage, partly on a local computing device and partly on a remotecomputer device or entirely on the remote computer device. In the latterscenario, the remote computer may be connected to the local computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider). In some embodiments, electronic circuitry including, forexample, programmable logic circuitry, field-programmable gate arrays(FPGA), or programmable logic arrays (PLA) may execute the computerreadable program instructions by utilizing state information of thecomputer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the operations/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to operate in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe operation/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement theoperations/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon theoperability involved. It will also be noted that each block of the blockdiagrams and/or flowchart illustration, and combinations of blocks inthe block diagrams and/or flowchart illustration, can be implemented byspecial purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of onemore other features, integers, steps, operations, element components,and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A method of leveraging one or more social networks to determine preferences and online activity of a user to improve advertising to at least one item embodied therewith, the method implemented by an advertising computer system comprising a processor and a memory, the method comprising: identifying and selecting, by the processor of the advertising computer system, a target criteria of a search entry from a search history associated with the online activity of the user, the identifying and the selecting of the target criteria of the search entry leveraging the online activity within a social network page of the one or more social networks, the search history comprises one or more searches for products, services and variations on those products and services related to the at least one item, the target criteria comprising two or more gift purpose instances selected from a target criteria list; analyzing a purchase history related to the user to modify the target criteria, which produces a modified criteria utilized by the advertising computer system to improve advertising to the at least one item; identifying, by the processor, an intended recipient based on the modified criteria and based on social information of the one or more social networks by: generating an intended recipient list based on the social information and the modified criteria, the intended recipient list identifying persons with relationships to the user, receiving a selection of an augmented search selection, filtering the intended recipient list based on the social information, one or more passive confirmations, and the modified criteria to produce a filtered list including the intended recipient, the one or more passive confirmations including at least the selection of an augmented search suggestion, and utilizing user information to generate a product database that is associated with each person of the filtered list; associating, by the processor, the at least one item with the intended recipient by: analyzing the social information and the target criteria, mapping multiple search products of the search history to multiple social events of the one or more social networks, and determining counts of the search products mapped to the multiple social events, where the counts indicate a user interest for a corresponding event, and determining an event from the multiple social events with a highest count that indicates a highest user interest in buying a gift; outputting, by the processor for the event with the highest count, advertisement information comprising an item suggestion list, the intended recipient, advertisement timing information, the at least one item with the intended recipient, and at least one of a plurality of advertisement recipients, each of which is related to enable the generation of a targeted advertisement, and the at least one item being utilized in the targeted advertisement; and generating the targeted advertisement of the at least one item associated with the intended recipient.
 2. The method of claim 1, wherein the identifying of the intended recipient based on the social information associated with the user and the target criteria further comprises: determining an associated one or more of entities, individuals, events, or situations from the search history.
 3. The method of claim 1, further comprising: receiving user information, the user information including the search history and the social information.
 4. The method of claim 1, further comprising: accessing a database in accordance with the social information, the modified criteria, and the intended recipient to produce an item suggestion list.
 5. The method of claim 1, further comprising: analyzing the social information, the modified criteria, and the intended recipient to determine the plurality of advertisement recipients. 